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Originality and diversity in the artificial evolution of melodies

Published: 12 July 2011 Publication History

Abstract

One of the greatest problems when using genetic algorithms to evolve melodies is creating an aesthetically conscious measure of fitness. In this paper, we describe a new approach with a minimum measure of fitness in which a set of good individuals is returned at the end of the process. Details about the implementation of a population of measures and some genetic operators are described in this work before an implicit way to evaluate fitness is given. We define a Takeover Matrix to measure the relationship between different generations and its compromise between originality and diversity. By means of this Takeover Matrix, the evolutionary process itself can be used as a criterion instead of using only ordinary individual measures of fitness. The results show the implications of using the proposed approach and demonstrate that the proposed algorithm is able to generate good sets of melodies. The algorithm can be used not only for developing new ideas but also to extend earlier created melodies with influence from the initial population.

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Cited By

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  • (2020)Evolutionary music: applying evolutionary computation to the art of creating musicGenetic Programming and Evolvable Machines10.1007/s10710-020-09380-721:1-2(55-85)Online publication date: 1-Jun-2020
  • (2016)Hybrid self-adaptive evolution strategies guided by neighborhood structures for combinatorial optimization problemsEvolutionary Computation10.1162/EVCO_a_0018724:4(637-666)Online publication date: 1-Dec-2016
  • (2012)Automatic evaluation methods in evolutionary musicProceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II10.1007/978-3-642-32964-7_46(458-467)Online publication date: 1-Sep-2012

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    cover image ACM Conferences
    GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation
    July 2011
    2140 pages
    ISBN:9781450305570
    DOI:10.1145/2001576
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 12 July 2011

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    Author Tags

    1. algorithmic composition
    2. computer music
    3. evolutionary music
    4. genetic algorithms

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    View all
    • (2020)Evolutionary music: applying evolutionary computation to the art of creating musicGenetic Programming and Evolvable Machines10.1007/s10710-020-09380-721:1-2(55-85)Online publication date: 1-Jun-2020
    • (2016)Hybrid self-adaptive evolution strategies guided by neighborhood structures for combinatorial optimization problemsEvolutionary Computation10.1162/EVCO_a_0018724:4(637-666)Online publication date: 1-Dec-2016
    • (2012)Automatic evaluation methods in evolutionary musicProceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II10.1007/978-3-642-32964-7_46(458-467)Online publication date: 1-Sep-2012

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